Peak Power Output

Two variations of the vertical jump - Squat Jump (SJ) Counter Movement Jump (CMJ)
Variables of interest: Flight Time (FT) and Peak Power Output (PPO).

50 SIM

## [1] "Flight Time Quick Look + Distribution, CMJ + SJ"

## 
##  Shapiro-Wilk normality test
## 
## data:  JTFT50$Flight.Time
## W = 0.95528, p-value = 0.08662
## [1] "p > 0.05 - normally distributed"
## [1] "SJ paired t.test no significant difference between measurments"
## 
##  Paired t-test
## 
## data:  SJ$PRE and SJ$POST
## t = 1.3375, df = 10, p-value = 0.2107
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -11.62335  46.53244
## sample estimates:
## mean of the differences 
##                17.45455
## [1] "CMJ paired t.test no significant difference between measurments"
## 
##  Paired t-test
## 
## data:  CMJ$PRE and CMJ$POST
## t = 1.1055, df = 10, p-value = 0.2948
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -16.32638  48.48275
## sample estimates:
## mean of the differences 
##                16.07818
## [1] "Peak Power Output Quick Look + Distribution, CMJ + SJ"

## 
##  Shapiro-Wilk normality test
## 
## data:  JTPPO50$Peak.Power
## W = 0.9685, p-value = 0.2675
## [1] "p > 0.05 - normally distributed"
## [1] "SJ paired t.test no significant difference between measurments"
## 
##  Paired t-test
## 
## data:  SJ$PRE and SJ$POST
## t = 1.2823, df = 10, p-value = 0.2287
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -172.4506  640.0245
## sample estimates:
## mean of the differences 
##                233.7869
## [1] "CMJ paired t.test no significant difference between measurments"
## 
##  Paired t-test
## 
## data:  CMJ$PRE and CMJ$POST
## t = 1.1746, df = 10, p-value = 0.2674
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -199.8825  645.6185
## sample estimates:
## mean of the differences 
##                 222.868
##  [1] 1.0071887 0.9773456 1.0283129 1.0585645 1.0180800       NaN 0.9908181
##  [8] 0.9994497 0.9790670 1.0269253 1.0390204 0.9918734       NaN       NaN
## 
##  Paired t-test
## 
## data:  EUR50$PRE and EUR50$POST
## t = -0.40547, df = 10, p-value = 0.6937
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.02988052  0.02067978
## sample estimates:
## mean of the differences 
##            -0.004600368
## [1] 1.010604
## [1] 1.015205

100 SIM

## [1] "Flight Time Quick Look + Distribution, CMJ + SJ"

## 
##  Shapiro-Wilk normality test
## 
## data:  JTFT100$Flight.Time
## W = 0.94732, p-value = 0.0265
## [1] "p < 0.05 - not normally distributed"
## [1] "SJ paired t.test no significant difference between measurments"
## 
##  Paired t-test
## 
## data:  SJ$PRE and SJ$POST
## t = 0.51513, df = 11, p-value = 0.6167
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -16.63325  26.79825
## sample estimates:
## mean of the differences 
##                  5.0825
## [1] "CMJ paired t.test no significant difference between measurments"
## 
##  Paired t-test
## 
## data:  CMJ$PRE and CMJ$POST
## t = 0.23551, df = 11, p-value = 0.8181
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -16.92808  20.98474
## sample estimates:
## mean of the differences 
##                2.028333
## [1] "Peak Power Output Quick Look + Distribution, CMJ + SJ"

## 
##  Shapiro-Wilk normality test
## 
## data:  JTPPO100$Peak.Power
## W = 0.97305, p-value = 0.3065
## [1] "p > 0.05 - normally distributed"
## [1] "SJ paired t.test no significant difference between measurments"
## 
##  Paired t-test
## 
## data:  SJ$PRE and SJ$POST
## t = -0.99327, df = 11, p-value = 0.3419
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -542.9198  205.2713
## sample estimates:
## mean of the differences 
##               -168.8243
## [1] "CMJ paired t.test no significant difference between measurments"
## 
##  Paired t-test
## 
## data:  CMJ$PRE and CMJ$POST
## t = -0.97351, df = 11, p-value = 0.3512
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -538.5386  208.2353
## sample estimates:
## mean of the differences 
##               -165.1517
## 
##  Paired t-test
## 
## data:  EUR100$PRE and EUR100$POST
## t = 0.13237, df = 11, p-value = 0.8971
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.02977120  0.03358127
## sample estimates:
## mean of the differences 
##             0.001905035
## [1] 1.013399
## [1] 1.013257

BLOOD LACTATE

Measured Throughout Innings: Pre, PowerPlay, Middle, Post
Change in Lactate as innings progresses?

50 SIM

## [1] "Quick look"

## [1] "Remove Outliers of incorrect collection: PRE >2 and all Phases >16"

## [1] "ANOVA effect of phase on [Lactate]"
##             Df Sum Sq Mean Sq F value Pr(>F)  
## LT50$Phase   3  107.3   35.77   4.441 0.0113 *
## Residuals   28  225.5    8.05                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "p < 0.05 significant effect of phases on lactate"

## [1] "Post-Hoc Test: Tukeys HSD"
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = LT50$Lactate ~ LT50$Phase)
## 
## $`LT50$Phase`
##                        diff        lwr      upr     p adj
## Power Play-Pre     3.533333 -0.6514693 7.718136 0.1209904
## Middle-Pre         5.173333  1.1718966 9.174770 0.0075079
## Post-Pre           4.370833  0.1860307 8.555636 0.0381441
## Middle-Power Play  1.640000 -2.0355543 5.315554 0.6207545
## Post-Power Play    0.837500 -3.0368744 4.711874 0.9342102
## Post-Middle       -0.802500 -4.4780543 2.873054 0.9323978

## Linear mixed model fit by REML. t-tests use Satterthwaite's method [
## lmerModLmerTest]
## Formula: Lactate ~ Phase + (1 | Subject.ID)
##    Data: LT50
## 
## REML criterion at convergence: 143.7
## 
## Scaled residuals: 
##     Min      1Q  Median      3Q     Max 
## -1.4180 -0.6372 -0.0020  0.6043  2.5422 
## 
## Random effects:
##  Groups     Name        Variance Std.Dev.
##  Subject.ID (Intercept) 2.331    1.527   
##  Residual               5.645    2.376   
## Number of obs: 32, groups:  Subject.ID, 11
## 
## Fixed effects:
##                 Estimate Std. Error     df t value Pr(>|t|)    
## (Intercept)        1.630      1.116 27.731   1.461 0.155327    
## PhasePower Play    3.637      1.321 20.674   2.753 0.012032 *  
## PhaseMiddle        5.082      1.261 20.655   4.032 0.000619 ***
## PhasePost          4.098      1.321 20.674   3.101 0.005476 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Correlation of Fixed Effects:
##             (Intr) PhsPwP PhsMdd
## PhasePwrPly -0.688              
## PhaseMiddle -0.727  0.599       
## PhasePost   -0.688  0.574  0.599

##     (Intercept) PhasePower Play     PhaseMiddle       PhasePost 
##        1.630466        3.637262        5.082245        4.097682

100 SIM

## [1] "QUICK LOOK"

## [1] "ANOVA: effect of Phase on [Lactate]"
##              Df Sum Sq Mean Sq F value   Pr(>F)    
## LT100$Phase.  3  217.2   72.40   8.754 0.000106 ***
## Residuals    46  380.5    8.27                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 2 observations deleted due to missingness
## [1] "p < 0.05 significant effect of phases on lactate"
## [1] "Post-Hoc Test: Tukeys HSD"
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = LT100$Lactate ~ LT100$Phase.)
## 
## $`LT100$Phase.`
##                        diff        lwr      upr     p adj
## Power Play-Pre    3.5307692  0.5240438 6.537495 0.0155020
## Middle-Pre        4.9833333  1.9146071 8.052060 0.0004530
## Post-Pre          5.1500000  2.0812737 8.218726 0.0002853
## Middle-Power Play 1.4525641 -1.6161622 4.521290 0.5915256
## Post-Power Play   1.6192308 -1.4494955 4.687957 0.5018572
## Post-Middle       0.1666667 -2.9628323 3.296166 0.9989643
## [1] "Remove Outliers of incorrect collection: PRE >2 and all Phases >16"
## [1] "ANOVA"
##              Df Sum Sq Mean Sq F value   Pr(>F)    
## LT100$Phase.  3  217.2   72.40   8.754 0.000106 ***
## Residuals    46  380.5    8.27                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "Post Hoc"
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = LT100$Lactate ~ LT100$Phase.)
## 
## $`LT100$Phase.`
##                        diff        lwr      upr     p adj
## Power Play-Pre    3.5307692  0.5240438 6.537495 0.0155020
## Middle-Pre        4.9833333  1.9146071 8.052060 0.0004530
## Post-Pre          5.1500000  2.0812737 8.218726 0.0002853
## Middle-Power Play 1.4525641 -1.6161622 4.521290 0.5915256
## Post-Power Play   1.6192308 -1.4494955 4.687957 0.5018572
## Post-Middle       0.1666667 -2.9628323 3.296166 0.9989643

## [1] "Subject.ID" "Phase."     "Lactate"

HEART RATE

Recorded throughout the innings at the end of each over

50 SIM

## [1] "Quick Look"

## [1] "Applied linear model"

## 
## Call:
## lm(formula = HR50$Heart.Rate ~ HR50$Over)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -40.938 -13.446   0.093  15.003  43.171 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 125.3600     3.2724   38.31  < 2e-16 ***
## HR50$Over     2.5782     0.3361    7.67 1.74e-12 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 18.7 on 156 degrees of freedom
##   (18 observations deleted due to missingness)
## Multiple R-squared:  0.2738, Adjusted R-squared:  0.2692 
## F-statistic: 58.83 on 1 and 156 DF,  p-value: 1.736e-12
## [1] "ANOVA"
##              Df Sum Sq Mean Sq F value   Pr(>F)    
## HR50$Over     1  20572   20572   58.83 1.74e-12 ***
## Residuals   156  54552     350                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 18 observations deleted due to missingness

100 SIM

## [1] "Quick look"

## [1] "Applied Linear model"

## 
## Call:
## lm(formula = HR100$Heart.Rate ~ HR100$Over)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -47.985 -12.440   0.502  15.188  36.387 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 133.6712     3.4729  38.490  < 2e-16 ***
## HR100$Over    2.3141     0.3614   6.404 2.84e-09 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 18.37 on 124 degrees of freedom
##   (50 observations deleted due to missingness)
## Multiple R-squared:  0.2485, Adjusted R-squared:  0.2425 
## F-statistic: 41.01 on 1 and 124 DF,  p-value: 2.841e-09
## [1] "ANOVA"
##              Df Sum Sq Mean Sq F value   Pr(>F)    
## HR100$Over    1  13845   13845   41.01 2.84e-09 ***
## Residuals   124  41863     338                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 50 observations deleted due to missingness

CHANGE IN MASS

Measured both with + w/o kit (pads, gloves etc.) pre and post simulation

50 SIM

## [1] "Quick Look"

## [1] "Change in weight with kit on - paired t.test"
## 
##  Paired t-test
## 
## data:  w_kit$PRE and w_kit$POST
## t = 5.6973, df = 10, p-value = 0.0001991
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.3653472 0.8346528
## sample estimates:
## mean of the differences 
##                     0.6
## [1] "Change in weight without kit - paired t.test"
## 
##  Paired t-test
## 
## data:  wo_kit$PRE and wo_kit$POST
## t = 6.4061, df = 10, p-value = 7.771e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.4150278 0.8576995
## sample estimates:
## mean of the differences 
##               0.6363636
## [1] "Significant change in weight between pre + post measures with + w/o kit"

100 SIM

## [1] "Quick Look"

## [1] "Change in weight with kit on - paired t.test"
## 
##  Paired t-test
## 
## data:  w_kit$PRE and w_kit$POST
## t = 7.1285, df = 10, p-value = 3.185e-05
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.3624646 0.6920808
## sample estimates:
## mean of the differences 
##               0.5272727
## [1] "Change in weight without kit - paired t.test"
## 
##  Paired t-test
## 
## data:  wo_kit$PRE and wo_kit$POST
## t = 10.198, df = 11, p-value = 6.076e-07
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.6992195 1.0841139
## sample estimates:
## mean of the differences 
##               0.8916667
## [1] "Significant change in weight between pre + post measures with + w/o kit"

MUSCULAR OUTPUT

Singles and doubles measured throughout simulation. One off-strike triple in both sims - not analyzed

Change in sprint time as innings progresses, seperated into on/off strike and run type for analysis.

50 SIM

## [1] "Quick Look"

## [1] "On Strike Singles"
## [1] "linear model"

## 
## Call:
## lm(formula = onsingle$Time ~ onsingle$Over)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.7976 -0.3944 -0.1409  0.1413  2.6212 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    2.36922    0.10770  21.998  < 2e-16 ***
## onsingle$Over  0.03574    0.01030   3.471 0.000617 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.5742 on 236 degrees of freedom
## Multiple R-squared:  0.04857,    Adjusted R-squared:  0.04454 
## F-statistic: 12.05 on 1 and 236 DF,  p-value: 0.0006165
## [1] "ANOVA"
##                Df Sum Sq Mean Sq F value   Pr(>F)    
## onsingle$Over   1   3.97   3.972   12.05 0.000617 ***
## Residuals     236  77.81   0.330                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "Significant effect of over # on sprint times"
## [1] "On Strike Doubles"
## [1] "linear model"

## 
## Call:
## lm(formula = ondouble$Time ~ ondouble$Over)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.2136 -0.3720 -0.1442  0.1852  2.3594 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    2.48519    0.20893  11.895   <2e-16 ***
## ondouble$Over  0.02280    0.02004   1.138    0.258    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.5554 on 96 degrees of freedom
## Multiple R-squared:  0.0133, Adjusted R-squared:  0.003022 
## F-statistic: 1.294 on 1 and 96 DF,  p-value: 0.2581
## [1] "ANOVA"
##               Df Sum Sq Mean Sq F value Pr(>F)
## ondouble$Over  1  0.399  0.3992   1.294  0.258
## Residuals     96 29.614  0.3085
## [1] "No significant effect of over # on sprint times"
## [1] "Off-Strike Singles"
## [1] "Linear model"

## 
## Call:
## lm(formula = offsingle$Time ~ offsingle$Over)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.60047 -0.24172 -0.06895  0.15486  2.00748 
## 
## Coefficients:
##                Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    2.354077   0.070988  33.162   <2e-16 ***
## offsingle$Over 0.013649   0.007017   1.945   0.0532 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.4074 on 190 degrees of freedom
## Multiple R-squared:  0.01953,    Adjusted R-squared:  0.01437 
## F-statistic: 3.784 on 1 and 190 DF,  p-value: 0.05322
## [1] "ANOVA"
##                 Df Sum Sq Mean Sq F value Pr(>F)  
## offsingle$Over   1  0.628  0.6282   3.784 0.0532 .
## Residuals      190 31.540  0.1660                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## [1] "No significant effect of over # on sprint times"
## [1] "Off-Strike Doubles"

## [1] "ANOVA"
##                Df Sum Sq Mean Sq F value Pr(>F)
## offdouble$Over  1  0.056 0.05639   0.192  0.664
## Residuals      40 11.765 0.29412
## [1] "No significant effect of over # on sprint times"

100 SIM

## [1] "Quick Look"

## [1] "On-Strike Singles"
## [1] "Linear Model"

## 
## Call:
## lm(formula = onsingle$Time ~ onsingle$Over)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.8780 -0.3033 -0.1146  0.1818  1.9991 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   2.591662   0.053930  48.056   <2e-16 ***
## onsingle$Over 0.011317   0.005669   1.996   0.0467 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.4431 on 337 degrees of freedom
## Multiple R-squared:  0.01169,    Adjusted R-squared:  0.008755 
## F-statistic: 3.985 on 1 and 337 DF,  p-value: 0.04671
## [1] "ANOVA"
## 
## Call:
## lm(formula = onsingle$Time ~ onsingle$Over)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.8780 -0.3033 -0.1146  0.1818  1.9991 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   2.591662   0.053930  48.056   <2e-16 ***
## onsingle$Over 0.011317   0.005669   1.996   0.0467 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.4431 on 337 degrees of freedom
## Multiple R-squared:  0.01169,    Adjusted R-squared:  0.008755 
## F-statistic: 3.985 on 1 and 337 DF,  p-value: 0.04671
## [1] "Significant effect of over # on sprint times"

## 
## Call:
## lm(formula = ondouble$Time ~ ondouble$Over)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.4253 -0.2835 -0.1083  0.1733  1.4818 
## 
## Coefficients:
##                Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   2.5696963  0.2792008   9.204 3.14e-14 ***
## ondouble$Over 0.0008768  0.0235745   0.037     0.97    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3794 on 81 degrees of freedom
## Multiple R-squared:  1.708e-05,  Adjusted R-squared:  -0.01233 
## F-statistic: 0.001383 on 1 and 81 DF,  p-value: 0.9704
##               Df Sum Sq Mean Sq F value Pr(>F)
## ondouble$Over  1   0.00  0.0002   0.001   0.97
## Residuals     81  11.66  0.1440
## [1] "No Significant effect of over # on sprint times"
## [1] "Off-Strike Singles"
## [1] "Linear Model"

## 
## Call:
## lm(formula = offsingle$Time ~ offsingle$Over)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.49578 -0.20521 -0.06421  0.17102  2.59091 
## 
## Coefficients:
##                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)    2.449e+00  4.856e-02  50.430   <2e-16 ***
## offsingle$Over 8.598e-05  5.257e-03   0.016    0.987    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3123 on 241 degrees of freedom
## Multiple R-squared:  1.11e-06,   Adjusted R-squared:  -0.004148 
## F-statistic: 0.0002675 on 1 and 241 DF,  p-value: 0.987
## [1] "ANOVA"
##                 Df Sum Sq Mean Sq F value Pr(>F)
## offsingle$Over   1    0.0 0.00003       0  0.987
## Residuals      241   23.5 0.09752
## [1] "No Significant effect of over # on sprint times"
## [1] "Off-Strike Doubles"

##                Df Sum Sq Mean Sq F value Pr(>F)
## offdouble$Over  1  0.004 0.00420   0.046  0.831
## Residuals      36  3.281 0.09114
## [1] "No Significant effect of over # on sprint times"

PSYCHOPHYSICAL - Rating of Perceived Exertion

Central RPE (Cardiovascular) + Local RPE (Legs) recorded at the end of every over

50 SIM

## [1] "Quick Look"

## [1] "Central RPE ANOVA"
##               Df Sum Sq Mean Sq F value   Pr(>F)    
## Central$Over   1  671.4   671.4   79.07 9.43e-16 ***
## Residuals    167 1417.9     8.5                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Post Hoc Tukeys HSD"
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Central$Score ~ Central$Phase)
## 
## $`Central$Phase`
##                            diff       lwr        upr     p adj
## Middle-Close Inn.    -0.6981132 -2.080754  0.6845274 0.4583633
## PowerPlay-Close Inn. -4.1563342 -5.482974 -2.8296944 0.0000000
## PowerPlay-Middle     -3.4582210 -4.784861 -2.1315812 0.0000000

## [1] "Local RPE ANOVA"
##              Df Sum Sq Mean Sq F value Pr(>F)    
## Local$Over    1  850.6   850.6   107.8 <2e-16 ***
## Residuals   167 1318.0     7.9                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 7 observations deleted due to missingness
## [1] "Post Hoc Tukeys HSD"
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Local$Score ~ Local$Phase)
## 
## $`Local$Phase`
##                           diff       lwr        upr     p adj
## Middle-Close Inn.    -1.471698 -2.824010 -0.1193867 0.0292936
## PowerPlay-Close Inn. -4.862234 -6.159773 -3.5646951 0.0000000
## PowerPlay-Middle     -3.390536 -4.688075 -2.0929970 0.0000000

100 SIM

## [1] "Quick Look"

## [1] "Central RPE ANOVA"
##               Df Sum Sq Mean Sq F value Pr(>F)    
## Central$Over   1  888.3   888.3   99.23 <2e-16 ***
## Residuals    202 1808.3     9.0                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 4 observations deleted due to missingness
## [1] "Post Hoc Tukeys HSD"
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Central$Score ~ Central$Phase)
## 
## $`Central$Phase`
##                           diff      lwr         upr     p adj
## Middle-Close Inn.    -1.250000 -2.54655  0.04654995 0.0614652
## PowerPlay-Close Inn. -4.476151 -5.72047 -3.23183305 0.0000000
## PowerPlay-Middle     -3.226151 -4.47047 -1.98183305 0.0000000

## [1] "Local RPE ANOVA"
##              Df Sum Sq Mean Sq F value Pr(>F)    
## Local$Over    1  753.2   753.2   152.2 <2e-16 ***
## Residuals   202 1000.0     5.0                   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 4 observations deleted due to missingness
## [1] "Post Hoc Tukeys HSD"
##   Tukey multiple comparisons of means
##     95% family-wise confidence level
## 
## Fit: aov(formula = Local$Score ~ Local$Phase)
## 
## $`Local$Phase`
##                           diff       lwr        upr     p adj
## Middle-Close Inn.    -1.546875 -2.525646 -0.5681038 0.0007213
## PowerPlay-Close Inn. -4.235197 -5.174539 -3.2958561 0.0000000
## PowerPlay-Middle     -2.688322 -3.627664 -1.7489811 0.0000000

## [1] "Difference between central + local?"

PREFRONTAL CORTEX IMAGING (FNIR)

Pre + Post measures during CogState testing. HBO - Oxygenated HGB
HBR - Deoxygenated HGB
HBT - Total HGB (HBO + HBR) OXY - Oxygenation (HBO - HBR).

CogState Battery
GMT - Groton Maze Learning Task
ONB - One Back Card memory
TWB - Two Back Card memory

50 SIM

## [1] "Quick Look"

## [1] "Lots of outliers. not altered for remaining stats"
## [1] "Averaged all optodes accross headband and determined average value for each task from markers in data"

## [1] "two-way ANOVA: Fixed Factors, CogState Task + Measurement period (Pre vs Post)"
##                          Df Sum Sq Mean Sq F value Pr(>F)
## avgHBO$Phase              1   11.6  11.577   1.068  0.307
## avgHBO$Task               2    2.4   1.208   0.111  0.895
## avgHBO$Phase:avgHBO$Task  2   29.6  14.804   1.366  0.266
## Residuals                44  477.0  10.841               
## 1 observation deleted due to missingness

## [1] "two-way ANOVA: Fixed Factors, CogState Task + Measurement period (Pre vs Post)"
##                          Df Sum Sq Mean Sq F value Pr(>F)
## avgHBR$Phase              1   13.8  13.802   1.226  0.274
## avgHBR$Task               2    1.4   0.705   0.063  0.939
## avgHBR$Phase:avgHBR$Task  2   18.2   9.114   0.809  0.452
## Residuals                44  495.5  11.260               
## 1 observation deleted due to missingness

100 SIM

## [1] "Quick Look"

## [1] "Lots of outliers. not altered for remaining stats"
## [1] "two-way ANOVA: Fixed Factors, CogState Task + Measurement period (Pre vs Post)"

##                          Df Sum Sq Mean Sq F value   Pr(>F)    
## avgHBO$Phase              1  96.78   96.78  16.135 0.000334 ***
## avgHBO$Task               2   3.16    1.58   0.263 0.770063    
## avgHBO$Phase:avgHBO$Task  2  21.22   10.61   1.769 0.186810    
## Residuals                32 191.93    6.00                     
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## [1] "two-way ANOVA: Fixed Factors, CogState Task + Measurement period (Pre vs Post)"
##                          Df Sum Sq Mean Sq F value Pr(>F)  
## avgHBR$Phase              1   51.4   51.39   3.865  0.058 .
## avgHBR$Task               2    4.6    2.32   0.175  0.841  
## avgHBR$Phase:avgHBR$Task  2    5.2    2.61   0.197  0.822  
## Residuals                32  425.4   13.29                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

CogState

GMT - ter (total # errors lower is better), cmv (correct moves) (speed accuracy trade off)

ONB - lmn (speed), acc (accuracy)

TWB - lmn (speed), acc (accuracy)

50 + 100 TO DO: 50 vs 100 comparisons (normal dist only)